Running no/low code Agentic AI
Build powerful, autonomous workflows without writing complex code. Connect APIs, orchestrate LLMs, and deploy multi-agent systems.
Full access to curriculum, live sessions, systems architecture guidance, and private cohort network.
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About this program
Speed matters. Why write custom Python orchestrators when you can visually string together powerful Agentic pipelines? In this cohort, you will learn to use industry-leading tools like Make.com, n8n, Flowise, and Zapier to build systems that read emails, make decisions, search databases, and update CRMs entirely autonomously.
Who is this for?
Founders, Marketers, Operations Managers, Consultants
What you'll actively build & learn
Understanding Fundamentals
Grasp the core mechanics of AI systems, from transformers to retrieval algorithms, moving beyond superficial APIs.
Production-Ready Architecture
Learn how to architect scalable, resilient generative AI applications that handle edge cases and high throughput.
Hands-on Engineering
Write custom PyTorch models, build multi-agent swarms using LangGraph, and deploy to Kubernetes.
Verifiable Execution
Complete rigorous capstone projects that serve as a proof-of-work portfolio for your next AI engineering role.
Time Commitment & Schedule
Live Engineering
2-3 hrs / week
Deep-dive interactive technical sessions focusing on architecture, code walkthroughs, and edge cases. Fully recorded.
Independent Build
4-6 hrs / week
Asynchronous reading materials, implementing weekly milestones, and collaborating via Discord for unblocking code errors.
Weekly Syllabus
Each week is structured around three things: what you'll cover, what capability you'll walk away with, and the concrete deliverable that moves you toward the final capstone.
4 weeks with practical workflow builds
A live autonomous workflow with business utility
Hands-on system assembly using no-code tools and guided reviews
The Sovereign Agent Ecosystem
- We discard the standard 'linear automation' mentality and introduce Agentic State Machines.
- You will dive deeply into n8n and Make.com as orchestrators, understanding precisely how to handle asynchronous webhook payloads, manage API rate limits, and structure looping mechanisms that allow agents to 'think' before acting.
Understand the building blocks of autonomous workflows.
A working orchestration flow in n8n or Make.
Advanced Prompt Routing & Memory
- LLMs are stateless engines; we must give them memory.
- We will build dynamic prompt templates that ingest live data.
- You'll implement deterministic routing logic based on LLM classification, ensuring workflows branch intelligently.
- We'll also construct simple key-value stores in databases to impart long-term memory across sessions.
Add routing, decision logic, and memory to your workflow.
A multi-step agent flow with branching and stored context.
No-Code Vector DBs & Semantic RAG
- Keyword search is dead.
- You will learn to build Retrieval-Augmented Generation (RAG) pipelines without writing python code.
- Using Flowise, we will chunk large PDF datasets, generate embeddings via OpenAI APIs, and store them in Pinecone.
- You will then connect this RAG engine to a Slack bot to answer internal company queries instantly.
Connect documents, retrieval, and chat into a usable assistant.
A no-code RAG assistant wired to a communication surface.
Autonomous CRM & Outbound Agent
- The capstone project combines all elements into a revenue-generating machine.
- You will architect an SDR (Sales Development Representative) agent that monitors incoming leads, scores the lead, drafts an ultra-personalized outreach message, and logs the entire interaction directly into HubSpot or Salesforce.
Ship a business-facing autonomous workflow with measurable value.
A capstone SDR-style agent connected to CRM tooling.
The syllabus builds toward a final proof of work.
The weekly syllabus is designed to stack toward a capstone that demonstrates what you can actually build. By the end of the cohort, you are not just finishing modules. You are presenting a concrete output that ties the learning arc together.
View Alumni CapstonesIndustry-Grade Certification
Earn a credential that actually matters. Every certificate is tied to your Capstone Project repo, valid for life, and optimized for your professional technical profile.
View Certification TiersEngineering Trust
Our alumni don't just 'use' AI. They architect the core infrastructure at forward-thinking engineering labs. This is a high-trust collective of senior talent.
"We've created a zero-noise environment for senior talent. This is where staff and principal engineers from Silicon Valley and beyond come to cross-pollinate their knowledge of agentic systems and distributed training."
The most technically rigorous program I've attended. No fluff, just pure architectural deep-dives into transformer blocks and swarm logic. This isn't just about calling APIs; it's about understanding the stochastic internals of LLMs.
LangGraph and Multi-agent orchestration was the missing link for our production pipeline. Highly recommended for senior devs who need to move beyond single-prompt engineering into complex, stateful workflows.
Direct 1:1 access to instructors who are actually shipping AI products. The focus on evaluations and evals-driven-dev is unique. We've implemented their RAG evaluation pipeline for our entire stealth startup.
Lead Instructor
Deep pedagogical philosophy balanced with production engineering rigor.
Meet
Anubhav
Anubhav is an AI solutions and engineering leader with two decades of global experience executing machine learning, generative AI, and physical intelligence initiatives.
With a proven track record of founding startups and building 0-to-1 engineering teams, he has architected and delivered production-grade systems across B2B SaaS, industrial robotics, sports tech, and massive-scale consumer streaming platforms serving over 600 million users.
At skilling academy, he personally mentors every student, bringing extensive experience in enterprise strategy, multi-agent workflows, computer vision, and scalable distributed architectures from the boardroom to the IDE.
Technical Expertise
- Transformers / Attention
- GNNs & Graph Search
- RLHF / DPO Alignment
- Distributed Training
- vLLM / NVIDIA Triton
- Kubernetes / Ray
- VectorDB Scaling
- Hybrid Retrieval
- Knowledge Graphs
- Autonomous Execution
- ReAct / Tool-use
- Planner Architectures
System FAQ
Addressing technical edge cases and curriculum logistics for the committed engineer.
Our cohorts are crafted for mid-to-senior level software engineers, data scientists, and technical product managers who are comfortable with Python and basic web architecture. If you've been 'prompt engineering' but want to understand the underlying mechanics—transformer blocks, vector algebra, and autonomous agent orchestration—this is for you.
Plan for 6-8 hours of focused effort per week. This breaks down into 2 hours of live, interactive deep-dives on Saturdays, 1 hour of midweek Q&A/Office Hours, and 3-5 hours of dedicated hands-on project implementation where you'll build production-ready AI modules.
Life happens. Every live session is recorded in 4K and uploaded to our private portal within 2 hours. You'll have lifetime access to these recordings, including all updated versions of the curriculum. Our Discord community and mentors are active 24/7 to help you get back on track.
Not necessarily. While we discuss hardware optimization, most of our practical work utilizes cloud-based environments (Google Colab, Modal, or Lambda Labs). We provide credits and setup guides so you can run large-scale inference and fine-tuning without burning through your own hardware.
We keep cohorts focused (max 60) to maintain a high mentor-to-student ratio. You’ll be split into smaller review pods, and you’ll get dedicated feedback via office hours and code review workflows. This keeps discussions high-bandwidth and practical.
We teach 'First Principles'. While we use popular frameworks for speed, we spend significant time building core components (like Custom RAG retrievers or ReAct loops) from scratch. This ensures that when the next big framework arrives, you'll understand exactly how it works under the hood.
Absolutely. Our final project is a portfolio-grade AI system that solves a real business problem. We also provide a dedicated session on the AI Engineering interview landscape, resume reviews for technical roles, and introductions to our network of hiring partners in the AI space.
We want you to be 100% satisfied. If after the first week you feel the cohort isn't the right fit, we offer a full, no-questions-asked refund. Our goal is to build a community of committed builders, and we stand by the quality of our curriculum.
Yes. All students get lifetime access to our internal repository of production-ready templates, deployment scripts, and evaluation benchmarks. These are the same tools our instructors use to build and scale AI solutions in their day-to-day professional work.
Upon successful submission and review of your final 3 project modules, you will receive a cryptographically signed digital certificate. This certificate is recognized by our network of partner companies and can be directly shared on LinkedIn or included in your professional portfolio.